Go binding for Onnxruntime C++ API. This is used by the Onnxruntime agent in MLModelScope to perform model inference in Go.
Download and install go-onnxruntime:
go get -v github.com/c3sr/go-onnxruntime
The binding requires Onnxruntime C++ and other Go packages.
The Go binding for Onnxruntime C++ API in this repository is built based on Onnxruntime v1.6.0.
To install Onnxruntime C++ on your system, you can follow the instruction on Onnxruntime Installation and refer to the dockerfiles.
The Onnxruntime C++ libraries are expected to be under /opt/onnxruntime/lib.
The Onnxruntime C++ header files are expected to be under /opt/onnxruntime/include.
If you get an error about not being able to write to /opt then perform the following:
sudo mkdir -p /opt/onnxruntime
sudo chown -R `whoami` /opt/onnxruntime
If you want to change the paths to the Onnxruntime C++ API, you need to also change the corresponding paths in lib.go .
You can install the dependency through using Dep.
dep ensure -v -vendor-only
This installs the dependencies in vendor/.
Configure the linker environmental variables since the Onnxruntime C++ library is under a non-system directory. Place the following in either your ~/.bashrc or ~/.zshrc file:
Linux
export LIBRARY_PATH=$LIBRARY_PATH:/opt/onnxruntime/lib
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/onnxruntime/lib
macOS
export LIBRARY_PATH=$LIBRARY_PATH:/opt/onnxruntime/lib
export DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:/opt/onnxruntime/lib
Run go build to check the dependencies, installation and library paths set-up.
On linux, the default is to use GPU, if you don't have a GPU, do go build -tags=nogpu instead of go build.
Note : The CGO interface passes go pointers to the C API. This is an error by the CGO runtime. Disable the error by placing:
export GODEBUG=cgocheck=0
in your ~/.bashrc or ~/.zshrc file and then run either source ~/.bashrc or source ~/.zshrc.
Examples of using the Go Onnxruntime binding to do model inference are under examples .
Some of the logic of conversion between Go types and Ort::Values is borrowed from go-pytorch.